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Baseball Betting and Sabermetrics (Part 1)

   by Hollywood Sports - 04/03/2013

The movie Moneyball brought sabermetrics to the general public last year. This term comes from the Society for American Baseball Research who began exploring deeper statistical analyses to assess individual player and team strength. Oakland A's general manager Billy Beane used advanced statistics to find value in under-appreciated baseball talent that did not stand-out when measured by conventional baseball statistics. While much attention is now devoted by baseball websites to use sabermetrics to assist baseball fans playing Rotisserie and Fantasy Baseball, I have used these advanced metrics to seize even bigger edges against the books and the general betting public whose faulty assumptions about the future expectations of starting pitchers creates inherent value in the money lines and Over/Unders that these books set with the goal of receiving equal action for baseball games.

Lets start with some underlying assumptions regarding how I bet and handicap baseball. Almost all of my attention is devoted to analyzing the competing starting pitchers in a game. It is pretty obvious that teams like the Texas Rangers are much better than teams like the Houston Astros. The problem is that most baseball bettors also appreciate this qualitative difference -- so the subsequent money-line takes these qualitative differences into account. Profiting from money-line betting requires identifying unique value relative to the established money line -- and the best way to do that is with looking deeper at the competing starting pitchers.

The most common three statistics that one will find for the day's starting pitchers from the sports page or from betting sheets "generously" offered by sport books are the following: Won/Loss Record, Earned Run Average, and WHIP (Walk + Hits per Innings Pitched). Sabermetricians typically scoff at relying too heavily on these numbers when predicting future performances for starting pitchers. Wins and losses are viewed with skepticism because (outside Clayton Kershaw's 8th inning home run for the Dodgers' Opening Day yesterday) starting pitchers have little control regarding how many runs his team will score. A starting pitcher who earns a Win despite allowing six runs does not look nearly as reliable looking forward as a tough-luck starting pitcher who lost a complete game by a 1-0 score. Earned Run Average and WHIP are better assessments regarding how effective a starting pitcher has performed since the goal of the pitcher is to limit runs -- and the more base runners allowed from hits and bases-on-balls, the more likely these base runners will then score. However, advanced statistics can dig deeper into why a starting pitcher is allowing the runs and hits he has allowed -- and the deeper truths that can be discerned from that analysis offers unique perspective in assessing whether those trends are likely to continue.

The biggest innovation to Sabermetrics regarding assessing future performances of pitchers is typically assigned to Voros McCracken. A graduate student at the time, McCracken argued that metrics like ERA and WHIP were inherently limited in assessing a pitcher's likely future performances because that pitcher has little to no control over what happens to the baseball once it is hit into play. From this, analyzing a pitcher's Batting Average on Balls in Play (BABIP) became a useful tool in assessing if that pitcher is seeing a disproportionately higher or lower number of balls ended up as hits or walks. The formula to determine a pitcher's (or hitter's) BABIP is: (Hits - Homeruns)/(At-Bats - Home Runs - Strikeouts + Sacrifice Flies). An assumption grew that pitchers who had unusually high BABIPs (relative to the MLB average) were not being served well by their defense while pitchers with unusually low BABIPs were very fortunate that more of the balls they were allowing into play did not sneak through for base hits. This metric offered exciting possibilities for bettors since it could identify starting pitchers who have been lucky or unlucky relative to these balls that they allowed into the playing field. Using this information, bettors may then have more accurate information to predict a starting pitcher's future performance than what W/L, ERA and WHIP have to offer that the general betting public.

Unfortunately, there were some fundamental flaws in McCracken's analysis. In fairness, he was not a baseball expert when offering his still useful insight. However, fantasy baseball experts continue to struggle to treat McCracken's original essay with the same level of scrutiny that exists in peer-reviewed academic environments. Instead, what has become typical is handwringing from baseball writers like ESPN Fantasy Baseball'sTristan Cockcroft who writes basically the same preseason article on BABIP every March. The genre works as follows: (1) invoke Sabermetrics regarding how advanced baseball statistics have gotten; (2) claim your superiority in assessing these statistics by ridiculing fantasy baseball hobbyists who misuse the metric; (3) identify a handful of counterfactuals that disprove the value in looking at a player's BABIP; (4) begin hedging the importance of the metric overall -- while also making sure to directly contradict an argument made in your previous year's article on Sabermetics; then (5) reassert once-again your self-proclaimed expertise on the subject (while optionally mentioning your success in one of the dozen fantasy leagues you played in one year).

Confusion over Sabermetrics like BABIP helps us continue to beat the books and the betting public when it comes to finding value in the money line. In fairness to Cockcroft, I do happen to find some of his work valuable (most notably, his study into how starting pitchers perform when returning from the disabled list). However, Cockcroft would disagree with my evolving use of the principles of BABIP -- and I remain very comfortable with that proposition. As opposed to working behind the cushy desks at the ESPN Bristol campus, baseball bettors are accountable for their predictions every day from April to October. The proof is in the pudding for my work as Hollywood Sports ended last season on a 60.4% winning clip for our last 240 baseball plays (139-91) playing money line underdogs, money-line favorites (never priced higher than -150), run-line favorites and underdogs and plenty of Over/Under plays where we ended the year on a 44-21 (68%) ML Totals run.

In Part Two of this essay, I will discuss how my looking specifically at BABIP for ground balls put into play (GB BABIP) and BABIP for line drives put into play (LD BABIP) has increased my baseball profits over the last two years. Best of luck -- Frank.

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